Text Classification
Transformers
Safetensors
bert
multilingual
multi-label-classification
community-notes
topic-classification
text-embeddings-inference
Instructions to use ychuai/community-notes-topic-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ychuai/community-notes-topic-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ychuai/community-notes-topic-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ychuai/community-notes-topic-classifier") model = AutoModelForSequenceClassification.from_pretrained("ychuai/community-notes-topic-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download topic_config.json from ychuai/community-notes-topic-classifier: direct link, hf CLI and curl.
- Browser
- Download file 516 Bytes
-
https://huggingface.co/ychuai/community-notes-topic-classifier/resolve/main/topic_config.json
- Command line
-
hf download hf://ychuai/community-notes-topic-classifier/topic_config.json
-
curl -L -o topic_config.json https://huggingface.co/ychuai/community-notes-topic-classifier/resolve/main/topic_config.json
516 Bytes
| { | |
| "pipeline_version": "post-with-all-notes-v1", | |
| "base_model": "Twitter/twhin-bert-base", | |
| "categories": [ | |
| "Politics and Elections", | |
| "War and Geopolitics", | |
| "Health and Medicine", | |
| "Economy and Finance", | |
| "Technology and AI", | |
| "Crime and Public Safety", | |
| "Sports and Games", | |
| "Celebrity and Entertainment", | |
| "Religion and Spirituality", | |
| "Gender and Identity" | |
| ], | |
| "threshold": 0.5, | |
| "max_length": 512, | |
| "stride": 64, | |
| "pooling": "max_logits", | |
| "gpt_model": "gpt-5.4-mini" | |
| } |